Innovative IoT Smart Lock System: Enhancing Security with Fingerprint and RFID Technology
DOI:
https://doi.org/10.56532/mjsat.v4i4.335Keywords:
Internet of Things, Smart door, NodeMCU ESP 8266, RFID , FingerprintAbstract
Security concerns in residential and working environments are more critical than ever, yet traditional door locks that rely on physical keys still hold significant vulnerabilities. Those key risks include loss, misplacement, or copying and may result in unauthorized access. Moving into Industry 4.0, there is great potential to integrate IoT technology to create a far more sophisticated and resilient door access system to handle such concerns. This paper analyze the design and development of a new IoT-based smart lock system enhancing security with fingerprint recognition, RFID technology, and application control via Wi-Fi as an additional to conventional lock such as kill switch and also front desk switch. In the discussed system, the ESP8266 microcontroller is used for wireless communication. Then, Virtuino IoT applications provided the function for real-time monitoring, while HiveMQ MQTT broker secured data transmissions. Therefore, the electromagnetic locking mechanism at the door was improved by using multi-layer access control. As mentioned, the methodology would provide an integration of critical hardware parts, such as NodeMCU ESP8266, Arduino Uno and electromagnetic locks, with robust software solutions in terms of secure communication and control. Once developed, the system architecture will be simulated and tested for its effectiveness in achieving better security and operational efficiency. The opted multi-layered security system can be beneficial to residential and working environment and is designed to overcome the limitations of conventional locks. Thus, enhancing the implementation of IoT-based security solutions in everyday life.
References
Chathuri Paranagama and Budditha Hettige, “A Review on Existing Smart Door Lock Systems,” 2022, doi: 10.13140/RG.2.2.18892.08325.
U. A. B. Norarzemi et al., “Development of Prototype Smart Door System With IoT Application,” vol. 1, no. 1, 2020.
A. A. Zainuddin, R. M. Nor, A. ’Aatieff A. Hussin, and M. N. M. Sazali, “MQTT-Enabled Smart Door Access System: Design and Implementation Using NodeMCU ESP 8266 and HiveMQ,” in 2023 IEEE 9th International Conference on Computing, Engineering and Design (ICCED), Kuala Lumpur, Malaysia: IEEE, Nov. 2023, pp. 1–6. doi: 10.1109/ICCED60214.2023.10425368.
N. P. I. Widiantari, N. Karna, Sussi, I. P. Y. N. Suparta, and I. K. Gowinda, “Implementation of Panic Button and Fingerprint Sensor on Security System RFID Using Internet of Things and e-KTP,” in 2022 International Conference on Information Technology Systems and Innovation (ICITSI), Bandung, Indonesia: IEEE, Nov. 2022, pp. 375–382. doi: 10.1109/ICITSI56531.2022.9971021.
S. Kaya, E. Aşkar Ayyildiz, and M. Ayyildiz, “Smart Door Lock Design With Internet of Things,” Int. J. 3D Print. Technol. Digit. Ind., vol. 6, no. 2, pp. 201–206, Aug. 2022, doi: 10.46519/ij3dptdi.1074468.
S. Fuada and H. Hendriyana, “UPISmartHome V.2.0 – A Consumer Product of Smart Home System with an ESP8266 as the Basis,” J. Commun., pp. 541–552, 2022, doi: 10.12720/jcm.17.7.541-552.
M. A. Al Rakib et al., “Fingerprint Based Smart Home Automation and Security System,” Eur. J. Eng. Technol. Res., vol. 7, no. 2, pp. 140–145, Apr. 2022, doi: 10.24018/ejeng.2022.7.2.2745.
N. K. Daulay and M. N. Alamsyah, “Monitoring Sistem Keamanan Pintu Menggunakan Rfid dan Fingerprint Berbasis Web dan Database,” Jusikom J. Sist. Komput. Musirawas, vol. 4, no. 02, pp. 85–92, Nov. 2019, doi: 10.32767/jusikom.v4i2.632.
J. W. Simatupang and R. W. Tambunan, “Security Door Lock Using Multi-Sensor System Based on RFID, Fingerprint, and Keypad,” in 2022 International Conference on Green Energy, Computing and Sustainable Technology (GECOST), Miri Sarawak, Malaysia: IEEE, Oct. 2022, pp. 453–457. doi: 10.1109/GECOST55694.2022.10010367.
G. Ju, C. Sim, C. Kim, and Y. Kim, “Development of a Quadruple Security System Combining Keypad, RFID, Fingerprint, and Bluetooth modules,” 2021.
Khan, M. R. B., Jidin, R., & Pasupuleti, J. (2016). Energy audit data for a resort island in the South China Sea. Data in brief, 6, 489-491. https://doi.org/10.1016/j.dib.2015.12.033
Khan, M. R. B., Jidin, R., & Pasupuleti, J. (2016). Data from renewable energy assessments for resort islands in the South China Sea. Data in brief, 6, 117-120. https://doi.org/10.1016/j.dib.2015.11.043
Zahraoui, Y., Alhamrouni, I., Mekhilef, S. and Khan, M.R.B., 2022. Machine learning algorithms used for short-term PV solar irradiation and temperature forecasting at microgrid. In Applications of AI and IOT in Renewable Energy (pp. 1-17). Academic Press https://doi.org/10.1016 /B978-0-323-91699-8.00001-2
Almeida, D., Pasupuleti, J., Raveendran, S. K., & Basir Khan, M. R. (2021). Performance evaluation of solar PV inverter controls for overvoltage mitigation in MV distribution networks. Electronics, 10(12), 1456. https://doi.org/10.3390/electronics10121456
Seet, C. C., Pasupuleti, J., & Khan, M. R. B. (2019). Optimal placement and sizing of distributed generation in distribution system using analytical method. International Journal of Recent Technology and Engineering, 8(4), 6357-6363. https://doi.org/10.35940/ijrte.D5120.118419
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Copyright (c) 2024 Ahmad Anwar Zainuddin, Ammar Daniel Abd Rahman, Rizal Mohd Nor, Amir Aatief Amir Hussin, Nik Nor Muhammad Saifudin Nik Mohd Kamal, Abu Ubaidah Shamsudin, Muhamad Syariff Sapuan

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